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Metabolomics-based translational Metabolomics-based translational biomarkers for Alzheimer’s Diseasebiomarkers for Alzheimer’s DiseaseEugenia Trushina, PhDEugenia Trushina, PhD

Mayo Clinic RochesterMayo Clinic Rochester

June 17, 2013June 17, 2013

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MetabolomicsMetabolomics• The study of low molecular weight The study of low molecular weight molecules (molecules (<1500 Da) or metabolites or metabolites found within cells and biological systems found within cells and biological systems on global level (metabolome)on global level (metabolome)• Measures changes downstream of Measures changes downstream of genomic, transcriptomic and proteomic genomic, transcriptomic and proteomic alterations and, therefore, is consideredalterations and, therefore, is consideredmore representative of the functional more representative of the functional state of a cellstate of a cell• Can measure hundreds to thousands Can measure hundreds to thousands of unique chemical entities providing of unique chemical entities providing an overall understanding of metabolisman overall understanding of metabolism• Metabolites are conserved across Metabolites are conserved across various animal species, facilitating the various animal species, facilitating the extrapolation of research findings in extrapolation of research findings in laboratory animals to humanslaboratory animals to humans• Is an integral part of system biologyIs an integral part of system biology

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1. Sample collection

2. Metabolite extraction

3. Metabolite separation

4. Metabolite identification

5. Data analysis and canonical pathway enrichment analysis (MPP, SIMCA-P, MetacoreTM)

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Identification of Altered Metabolic Pathways in PlasmaIdentification of Altered Metabolic Pathways in Plasmaand CSF in Mild Cognitive Impairment and Alzheimer’sand CSF in Mild Cognitive Impairment and Alzheimer’s

Disease Using MetabolomicsDisease Using Metabolomics E. Trushina, T. Dutta, X-M. T. Persson, M. M. Mielke, R. C. Petersen E. Trushina, T. Dutta, X-M. T. Persson, M. M. Mielke, R. C. Petersen

PLoS ONE 8(5): e63644.PLoS ONE 8(5): e63644.

Mayo Clinic Study of Aging and ADRC

CSF andplasma

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PLASMAPLASMA CSFCSF

MC

I vs

CN

MC

I vs

CN

AD

vs

CN

AD

vs

CN

AD

vs

MC

IA

D v

s M

CI

plas

ma

plas

ma

CS

FC

SF

MCI

AD CN

MCI

AD CN

orthogonal two partial least squares-discriminant analysis (O2PLS-DA)Unsupervised Principal Component Analysis (PCA)

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Plasma CSFLysine

Androstenedione and testosterone

TCA cycle

Saturated fatty acid

Mitochondrial ketone bodies

Estrone

Prostaglandin 2

Aminoacyl-tRNA BS in cytoplasm

TryptophanLeucine, isoleucine and valine

Neurophysiological process_ Melatonin signaling

PyruvateSerotonin-melatonin

GABA

Cholesterol

Phospholipid p. 1

Butanoate

Plasmalogen

Propionate

Pyruvate/rodent version

Phenylalanine

Polyamine

(L)-Arginine

TCA cycle

Nicotine MB in liver

Aldosterone

Seratonin-melatonin

Cortisone

Prostaglandin 2

Methionine-cysteine-glutamate

Aspartate and asparagine

Vitamin B6

Histidine-glutamate-glutamine

Arginine/rodent version

Tryptophan

Urea cycle

Ascorbate

Vitamin B7 (biotin)

Cholesterol

Sulfur

Alanine, (L)-cysteine, (L)-methionine

Pyruvate/rodent version

-log(p-value) -log(p-value)

Role of Diethylhexyl Phthalate and Tributyltin in fat differentiation

6/853/41

3/513/69

2/272/353/943/973/1012/422/43

2/492/512/532/54

2/612/632/642/662/662/672/682/76

7/51

7/565/41

5/51

5/56

6/944/43

5/73

3/30

5/95

5/97

5/101

4/702/183/47

4/883/52

3/562/29

3/66

Metabolic changes in MCI vs. CNMetabolic changes in MCI vs. CN

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Plasma CSF

-log(p-value) -log(p-value)

Cholesterol and sphingolipids transportVitamin D2Polyamine

Intracellular cholesterol transport(L)-Arginine

Beta-alanineAspartate and aspargine

CortisoneGalactose

Lipid metabolism

FXR-regulated cholesterol and bile acid transport

Glycolysis and gluconeogenesisCholesterol

Bile acidRegulation of CFTR gating

Role of VDR in regulation of genes involved in osteoporosis

Vitamin D3 metabolic C-23 and C-24 pathwaysTriacylglycerol BS in obesity and diabetes mellitus, type II

Muscle contraction_nNOS signaling in skeletal muscles

Niacin-HDLAminoacyl-tRNA biosynthesis in mitochondria

Triacylglycerol metabolism p.2

Urea cycle

Lysine

TCA cycle

Prostaglandin 2

Aminoacyl-tRNA BS in cytoplasm

Androstenedione and testosterone

Alanine, (L)-cysteine, (L)-methionine

Mechanism of action of DGAT1 in obesity and diabetes mellitus, type II

Methionine-cysteine-glutamate

Cortisol BS from cholesterolRegulation of lipid MB_FXR-dependent negative-feedback regulation of bile acid concentration

RiboflavinAcetylcholine

Fructose

Tryptophan

Development_Activation of astroglia cell proliferation by ACM3Fatty Acid Omega Oxidation

Methionine

Cholesterol and sphingolipids transport

Intracellular cholesterol transport

(L)-Arginine

Histidine-glutamate-glutamine

Aspartate and aspargine

Cortisone

Ascorbate

Mitochondrial ketone bodies

Nicotine metabolism in liver

Glycolysis and gluconeogenesis

Cholesterol and sphingolipids transport/transport from Golgi

Bile acid

Regulation of CFTR gating

HETE and HPETEFXR-regulated cholesterol and bile acid cellular transport Pyruvate

Propionate

Urea cycle

Estrone

TCA cycle

Prostaglandin 2

Saturated fatty acids

Serotonin-melatonin

UMP

(L)-Alanine, (L)-cysteine, (L)-methionine

Cortisol BS from cholesterol

GABA

Glycine, serine, cysteine and threonine

Beta-Alanine

Tryptophan

8/207/389/689/70

9/908/76

5/357/738/946/566/596/595/41

8/20

7/855/467/887/944/33

4/353/20

4/41 5/56

3/24 6/80

4/476/94

5/66

3/28 3/27

5/745/69

5/66

3/313/31

7/123

2/143/333/34

3/31

5/42

5/565/61

3/24

4/43

3/28

6/97

6/101

3/32

3/34

4/51

13/948/51

9/738/709/908/764/185/33

6/516/565/41

4/327/94

4/42

6/95

6/1014/534/563/35

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Differentiating pathwaysDifferentiating pathways

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ConclusionsConclusions

• Metabolomics offers novel approach to identify alterations in multiple biochemical networks over the course of AD

• It allows identification of both expected and non-expected changes in biochemical pathways in animal models of AD and in human samples

• Metabolic signatures in CSF and plasma correlate with AD severity

• Metabolic signatures in plasma accurately reflect changes in CSF: MCI: 30% of the pathways altered in CSF and plasma were the sameAD: 60% of the pathways affected in CSF and plasma were the same

• Application of metabolomics in conjunction with other currently available tests could increase early AD diagnosis

• Metabolomics could be conducted in readily available fluids such as blood making it attractive for clinical application

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Future DirectionsFuture Directions

• Studies in larger patient cohorts are needed

• Test and sample validation studies need to be included in every project

• Acquisition of the data using multiple analytical platforms should increase the accuracy and reproducibility

• Additional research is needed to reveal the role of metabolites linked to AD pathology in the mechanisms of normal aging